Data Scientist

Job Description:

We are looking for a talented Data Scientist to design and implement algorithms and solutions for processing images from optical sensors and Synthetic Aperture Radar (SAR) sensors, mainly focused for agriculture and forestry applications. The ideal candidate will be involved in developing and prototyping advanced algorithms that leverage state-of-the-art technologies in remote sensing data processing and machine learning to extract meaningful insights from large volumes of data.

Responsibilities

• Algorithm Development: Create and optimize algorithms for data extraction, filtering, and enhancement of satellite images, and analysis of multivariate time series of satellite images, using advanced techniques (Machine Learning and Deep Learning) as classification, semantic segmentation and feature extraction
• Programming and Coding: Develop software using languages such as Python. Knowledge of API development and of cloud platforms (AWS, Azure, or GCP) is a plus

Key Activities

• Design algorithms for image processing related to satellite images (SAR and optical)
• Write efficient code for implementing algorithms and software functionalities to support image processing and information extraction
• Supervise service development phases from concept through deployment, ensuring that project timelines and quality standards are met

Qualifications

• Programming skills in Python. Experience with libraries such as GDAL, Geopandas is a plus
• Hands-on experience with image processing, satellite data analysis, or similar technical field
• Experience in machine learning and deep learning frameworks (e.g., TensorFlow, PyTorch) for processing and analyzing satellite images
• Strong problem-solving skills and the ability to handle large-scale dataset
• Ability to work independently and within a team to manage multiple development stages, including planning, coding, testing, and deployment

Seniority:

Junior

Primary Location:

IT - Roma - Via Tiburtina, 965

Contract Type:

Permanent

Hybrid Working:

Hybrid